code: def get_circles(n_clusters):
      X, labels = make_circles(
          n_samples=N_SAMPLES, factor=0.5, noise=0.05, random_state=SEED
      )
      return normalize(X), labels
  
imports: import gradio
  import math
  from functools import partial
  import matplotlib.pyplot
  import numpy
  from sklearn.cluster import AgglomerativeClustering, Birch, DBSCAN, KMeans, MeanShift, OPTICS, SpectralClustering, estimate_bandwidth
  from sklearn.datasets import make_blobs, make_circles, make_moons
  from sklearn.mixture import GaussianMixture
  from sklearn.neighbors import kneighbors_graph
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 3 for calling a global function with example usage: get_circles(n_clusters) and returns: normalize,  labels